Literature DB >> 24496185

Big data in nephrology: friend or foe?

Terry Ketchersid1.   

Abstract

The phrase 'big data' has arrived in today's lexicon with great fanfare and some degree of hyperbole. Generally speaking, big data refer to data sets that are too complex to be successfully interrogated using standard statistical software. A wide variety of business sectors has utilized big data to garner competitive advantage within their respective markets. Medicine and nephrology, in particular, have been late to this table. This is beginning to change, however, as data scientists begin to work with these large data sets, developing predictive models that permit us to peer into the future. Coupled with an expanding understanding of genomics, predictive models constructed with the assistance of big data may soon provide us with a powerful tool to use as we provide care to patients with renal disease.
© 2013 S. Karger AG, Basel.

Entities:  

Mesh:

Year:  2013        PMID: 24496185     DOI: 10.1159/000356751

Source DB:  PubMed          Journal:  Blood Purif        ISSN: 0253-5068            Impact factor:   2.614


  3 in total

Review 1.  Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy.

Authors:  Miguel Hueso; Alfredo Vellido; Nuria Montero; Carlo Barbieri; Rosa Ramos; Manuel Angoso; Josep Maria Cruzado; Anders Jonsson
Journal:  Kidney Dis (Basel)       Date:  2018-01-25

Review 2.  Toward a Literature-Driven Definition of Big Data in Healthcare.

Authors:  Emilie Baro; Samuel Degoul; Régis Beuscart; Emmanuel Chazard
Journal:  Biomed Res Int       Date:  2015-06-02       Impact factor: 3.411

3.  Medical big data: promise and challenges.

Authors:  Choong Ho Lee; Hyung-Jin Yoon
Journal:  Kidney Res Clin Pract       Date:  2017-03-31
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.